Databricks' dolly-v2-12b vs Gopher

Databricks introduces dolly-v2-12b, an inventive language model providing high-quality, instruction-following capabilities. This 12-billion-parameter model is built on Pythia-12b, yielding exceptional performance, not inherent in its foundational model. Dolly-v2-12b is optimized for commercial use, having been fine-tuned on a diverse mix of instructions covering areas like brainstorming, classification, and summarization. While it may not be at the forefront of AI models, its proficiency in instruction adherence is remarkable. Available in varying sizes, dolly-v2-12b is complemented by the smaller dolly-v2-7b and dolly-v2-3b models. Users can leverage this model easily with Transformers and PyTorch using the Hugging Face platform, tapping into the practical insights and extensive dataset, databricks-dolly-15k, to power their AI applications.

Discover the cutting-edge advancements in artificial intelligence with DeepMind's exploration of language processing capabilities in AI. At the heart of this exploration is Gopher, a 280-billion-parameter language model designed to understand and generate human-like text. Language serves as the core of human intelligence, enabling us to express thoughts, create memories, and foster understanding.

Realizing its importance, DeepMind's interdisciplinary teams have endeavored to drive the development of language models like Gopher, balancing innovation with ethical considerations and safety. Learn how these language models are advancing AI research by enhancing performance in tasks ranging from reading comprehension to fact-checking while identifying limitations such as logical reasoning challenges. Attention is also given to the potential ethical and social risks associated with large language models, including the propagation of biases and misinformation, and the steps being taken to mitigate these risks.